Open Science and
Research Software Engineering

Workshop
Center for Advanced Internet Studies (CAIS)

Quirin Würschinger
q.wuerschinger@lmu.de

LMU Munich

September 21, 2023

Introduction

Workshop materials

> whoami

Quirin Würschinger
q.wuerschinger@lmu.de
Wissenschaftlicher Mitarbeiter and PostDoc in (computational) linguistics
LMU Munich

Current work

  • research
    • lexical innovation on the web and in social networks
    • variation and change in language use and social polarization in social networks
    • using Large Language Models (LLMs) like ChatGPT for research in linguistics and social science.
  • teaching: corpus linguistics and research methodology

Promoting Open Science in (computational) linguistics at LMU

  • teaching and applying reproducible corpuslinguistic methods
  • creating and sharing corpora among researchers and students

Topics

  • Open Science: What is it and why does it make sense?
  • Project setup: Learn to efficiently organize your project’s files and folders.
  • Data, code, and document management: Understand how to effectively manage and maintain your data, code, and documents.
  • Utilizing different data types: Discover how to work with various data types, such as interviews, web, and social media data.
  • Publication process: Learn about options for publishing your data, code, and documents.

Time table

Topic Start End
Intro 09:00 09:30
Open Science principles 09:30 10:30
— 10:30 10:50
version control 10:50 11:10
project structure 11:10 12:00
data 12:00 12:30
— 12:30 13:30
code 13:30 14:00
methods 14:00 14:30
authoring 14:30 15:15
— 15:15 15:30
publishing 15:30 16:00
open issues and recap 16:00 16:30

Addressing different backgrounds and goals

Backgrounds and interests

CAIS: Forschung zu Digitalisierung und Digitale Gesellschaft

Fachrichtungen

  • Politikwissenschaft
  • Erziehungswissenschaft
  • Kommunikationswissenschaft
  • Soziologie
  • …

Daten und Methoden

  • qualitativen Interviews
  • Textanalysen
  • quantitativen Befragungen
  • experimentellen Designs
  • Online-Plattformen/Social Media
  • …

Main interests

  • reproducible workflows
    • managing files and folders
    • plain text authoring
    • programming with Python and R
  • methods
    • quantitative approaches
    • text analysis
    • questionnaires
  • publishing
    • papers
    • code and data

Who are you?

  1. name
  2. place and position
  3. your research interest in about 3 sentences for someone outside your field

Dance your PhD

Open Science principles

What is Open Science

Why should we do Open Science?

Richard McElreath: Science as Amateur Software Development

source

source

source

source

Principles of Open Science

Center for Open Science

Open Science lifecycle

Center for Open Science

Roles in Open Science

Funders
make open science part of the selection process, and conditions for grantees conducting research.
Publishers
make open science part of the review process, and conditions for articles published in their journals.
Institutions
make open science part of academic training, and part of the selection process for research positions and evaluation for advancement and promotion.
Societies
make open science part of their awards, events, and scholarly norms.
Researchers
enact open science in their work and advocate for broader adoption in their communities.

[Center for Open Science]

Who profits from Open Science?

source

What is Open Science to you?

What do you find interesting, important, or attractive about Open Science?

https://tinyurl.com/opnsci

Learning outcomes

Implementing an open and reproducible workflow

  1. version control
  2. project structure
  3. data
  4. methods
  5. code
  6. authoring
  7. publishing

Break

Taking notes

Networked notes

  • logseq
  • Obsidian

Version control

Why use version control?

source

git and GitHub/GitLab

git
software on your machine 

git add scr/tests.py
git commit -m 'add tests'
git push
GitHub and GitLab
services on a remote server

git commands

(source)

Collaborating using GitHub

(source)

GitHub workflow

(source)

How to set up a GitHub repository

create a repository on GitHub

  1. (create GitHub account)
  2. click on New (https://github.com/new)
  3. specify repo name 1
  4. specify description
  5. specify visibility: private or public
  6. select Add a README file
  7. specify licence 2

clone the repository

go to the folder where you want your project to live

git clone https://github.com/wuqui/opensciws.git

add changes

commit changes

push changes

Project structure

source Let’s not pretend we’re all geniuses …

File names

File names should be:

  • Machine readable
  • Human readable
  • Optional: Consistent
  • Optional: Play well with default ordering

File structure

.
├── analysis            <- all things data analysis
│   └── src             <- functions and other source files
├── comm
│   ├── internal-comm   <- internal communication such as meeting notes
│   └── journal-comm    <- communication with the journal, e.g. peer review
├── data
│   ├── data_clean      <- clean version of the data
│   └── data_raw        <- raw data (don't touch)
├── dissemination
│   ├── manuscripts
│   ├── posters
│   └── presentations
├── documentation       <- documentation, e.g. data management plan
└── misc                <- miscellaneous files that don't fit elsewhere

 

tree DIR

cookie cutters

Practice: managing files and folders

Data

FAIR data

source

Types of data

  • interviews
  • questionnaires
  • web
  • social media

Code

Reproducibility et al.

The Turing Way

source

notebooks and literate programming

  • Knuth
    • application
      • R
      • Python: nbdev

Licensing

Code

https://choosealicense.com

Other materials

https://creativecommons.org/choose/

Authoring

Authoring
How can we organise our project from the beginning so that we can publish outputs in the end?
Publishing
Where can I publish my work (platforms, research centers infrastructure, …)?

Plain text

Quarto

  • single source → multiple output formats
    • PDF for publication outlets
    • blog
    • website

Publishing

How: How can we organise our project from the beginning so that we can publish outputs in the end? Where: Where can I publish my work (platforms, research centers infrastructure, …)?

Pre-registration

source

source

Outlets

ArXiV
preprints
Zenodo
all kinds including data, code, preprints, etc.
GitHub and GitLab
code, software
Open Science Framework
all kinds including data, code, preprints, preregistration, etc.
Software Heritage
archival of code (long-term)
Papers with Code
code and data for and with papers, mostly Machine Learning
…

Resources

  • DRA
  • The Turing Way
  • Data Carpentries